code: def central_errors(f, num, ndim, label=None):
      """Build DataFrame of approximation errors with central differences method."""
      points, w = grid(num, ndim)
      values = f(points)
  
      def name_errors():
          for ds, name in derivative_names(ndim):
              actual = autograd(f, ds, points)
              approx = central(values, ds, w)
              yield name, np.abs(actual - approx)
  
      return _build_errors_df(name_errors(), label)
  
file_path: tf-quant-finance/tf_quant_finance/experimental/finite_difference/methods.py
imports: from autograd import elementwise_grad
  import autograd.numpy
  import pandas
  import sobol_seq
label_desc: Use image node_id 10 for calling a global function with example usage: central_errors(f, num, ndim, label) and returns: _build_errors_df